Methods › General › Neural Architecture Search › Aging Evolution

Aging Evolution

3 papers tagged archive 2025-07-28

Introduced by Esteban Real et al. in Regularized Evolution for Image Classifier Architecture Search

archive 2025-07-28 Description, source and code snippet are the archive's method entry.

Aging Evolution, or Regularized Evolution, is an evolutionary algorithm for neural architecture search. Whereas in tournament selection, the best architectures are kept, in aging evolution we associate each genotype with an age, and bias the tournament selection to choose the younger genotypes. In the context of architecture search, aging evolution allows us to explore the search space more, instead of zooming in on good models too early, as non-aging evolution would.

PaperSource

Papers archive 2025-07-28

3 shown of 3, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.

Tasks archive 2025-07-28

6 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.

TaskPapers
Neural Architecture Search3
AutoML1
Bayesian Optimization1
Evolutionary Algorithms1
Image Classification1
Reinforcement Learning1

Usage over time archive 2025-07-28

Papers per year tagged with Aging Evolution: 2018 to 2021, peak 1 1 0 2018: 1 paper 2018 2019: 0 papers 2019 2020: 1 paper 2020 2021: 1 paper 2021
Papers per year the archive tags with this method, by the paper's archive date (3 dated). Bars are counts, not a trend claim.

Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).

Categories archive 2025-07-28

Neural Architecture Search

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